Triple

T8418695
Position Surface form Disambiguated ID Type / Status
Subject DICOM Application Entity E198793 entity
Predicate hasAbbreviation P43 FINISHED
Object AE
AE is the standard abbreviation for a DICOM Application Entity, which represents a logical device or software component that exchanges medical imaging data within a DICOM network.
 E732153 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: AE | Statement: [DICOM Application Entity, hasAbbreviation, AE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AE
Context triple: [DICOM Application Entity, hasAbbreviation, AE]
  • A. AE
    AE is the commonly used abbreviation for Academia Europaea, a European non-governmental association of scientists and scholars across all disciplines.
  • B. AE
    AE is the IATA airline designator assigned to Mandarin Airlines, a regional carrier based in Taiwan.
  • C. ALE
    ALE is a widely used research platform that provides a common interface to hundreds of Atari 2600 games for developing and evaluating artificial intelligence and reinforcement learning algorithms.
  • D. ARE
    ARE is the station code for Arendal Station, a railway station in the town of Arendal in Agder county, Norway.
  • E. ARE
    ARE is a professional licensure examination for architects in the United States that assesses candidates’ knowledge and skills required for independent practice.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: AE
Triple: [DICOM Application Entity, hasAbbreviation, AE]
Generated description
AE is the standard abbreviation for a DICOM Application Entity, which represents a logical device or software component that exchanges medical imaging data within a DICOM network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AE
Target entity description: AE is the standard abbreviation for a DICOM Application Entity, which represents a logical device or software component that exchanges medical imaging data within a DICOM network.
  • A. AE
    AE is the commonly used abbreviation for Academia Europaea, a European non-governmental association of scientists and scholars across all disciplines.
  • B. AE
    AE is the IATA airline designator assigned to Mandarin Airlines, a regional carrier based in Taiwan.
  • C. ALE
    ALE is a widely used research platform that provides a common interface to hundreds of Atari 2600 games for developing and evaluating artificial intelligence and reinforcement learning algorithms.
  • D. ARE
    ARE is the station code for Arendal Station, a railway station in the town of Arendal in Agder county, Norway.
  • E. ARE
    ARE is a professional licensure examination for architects in the United States that assesses candidates’ knowledge and skills required for independent practice.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca8312d63c8190bf133b676b44a385 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb84c7d6e48190a2bbde89c5d42af6 completed March 31, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce033df9c48190a8ec6b9347ba6e81 completed April 2, 2026, 5:48 a.m.
NEDg Description generation batch_69ce0782b0dc8190bf971eacb3b4582c completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce0854ce788190a209f229d504c038 completed April 2, 2026, 6:10 a.m.
Created at: March 30, 2026, 6:06 p.m.